USU researcher responds to Rep. Herrod

There is an old adage in statistics that states: "All models are wrong. Some are useful."

First articulated by George Box, a rather famous statistician, it reflects agreement among those who use statistics to model everything from business to economics to engineering to biological systems that error exists in any and all modeling exercises.

This includes, naturally, climate forecast models.

But it also includes the types of models that Rep. Chris Herrod, R-Provo, used to posit rather large increases in Provo electricity bills were a cap-and-trade program, one of several approaches being considered to reduce climate change impacts, actually implemented.

So I return Herrod's question back to him: "Where's the 'science' behind the dire estimates of $2,500-$4,000 annual increases in energy costs for Provo households? Assuming Herrod obtained his figures from a frequently cited cap-and-trade study by MIT, he simply divided the number of U.S. households into the estimated $366 billion cost over a 35-year period, arriving at the figure of about $3,100 annual cost. This is the middle of his range. He is certainly justified in adding a fudge factor for Provo's dependence on coal.

However, one of the MIT report authors, J. Reilly, says using such simple approaches is bad math, and that national annual increases are likely in the range of $800. Even when adding an unknown coal fudge factor, these estimates are well below the lower end of Herrod's range. By way of additional comparisons, the Environmental Protection Agency estimates are less than $150 annually, those of the Republican Heritage Foundation about $1,500, and the Congressional Budget Office about $1,600 per year.

I suspect, were I to invest my time into it, I could use the skills I have in 20-plus years of statistical modeling to posit an increase at least one order of magnitude smaller than that Herrod refers to, and more in line with that of MIT report author Reilly. Mine would simply be, perhaps, a minority model that more than 95 percent of others might disagree with, it being on the low end of defensible, science-based estimates.

Would Herrod then give my minority economic model the same weight he seemingly gives to Roy Spencer's minority model regarding climate change effects? I doubt it, given his supports a particular ideology and biases Herrod (at least honestly) acknowledges, while mine does not. Mine is just another model.

But the example highlights an underlying concern too frequently ignored in the current debate over the economic impacts of adjusting high energy-use lifestyles such as ours to reduce climate change effects: Why do policymakers such as Herrod routinely challenge and dismiss modeled climate forecasts, then turn around and use the same general classes of statistical models to estimate negative economic impacts?

You can't have it both ways. Herrod, as an elected decision-maker, cannot dismiss one set of statistical models while using others, particularly given that when eventually teased apart, all of the models -- be they business or economic or engineering or biological -- share common underlying mathematical algorithms.

So I ask again, where's the science behind these economic models Herrod and others use to say that climate change is an environmental sham? Why does he believe the economic science he references, and the "catastrophic" economic projections it makes, while dismissing climate models based on similar analytical approaches? Like he said, please convince me.

But perhaps we can all agree on one thing -- that all the models are wrong, it's just that some are useful. And it is here that Herrod is failing as a leader.

I worry about my children and children's children. I do not, as he apparently does, accept a simple do-nothing attitude reflecting an ideology that all climate change is inevitable and that our only response should be to stick our heads in the metaphorical sand and live merrily on.

Thomas C. Edwards is a research ecologist and professor at Utah State University in Logan.